A HYBRID MODEL FOR KNOWLEDGE ACQUISITION USING HIERARCHICAL CLUSTER ANALYSIS

by M.A.Shouman, M.G.Abou-Ali, and M.A.Mostafa .

Abstract: : The research in any discipline is heavily dependent on the quality of data collected and the meaning which subsequent analysis reveals. The research in Information Systems (IS) is based upon data collected by means of questionnaires, interviews, and observation. Inexperienced researchers find questionnaires and interviews attractive as a data gathering methodology. Many researchers have discovered that it is not simple to draft a good questionnaire because their answers are very superficial which impacts negatively on the quality of the research. Interviewing provides richer data and hence overcomes some of the problems of questionnaires, but still leaves the researcher with few guidelines. This paper explores a technique of the most valuable and flexible forms of knowledge acquisition techniques called Repertory Grid as an alternative method for gathering meaningful data. In this paper, the history of Repertory Grid, its objectives, components, mechanism, strengths and weaknesses are presented. Also, a hybrid model between questionnaire technique and Repertory Grid technique is presented. This model uses questionnaire as a primary data gathering technique then the acquired data are automatically transferred to the Repertory Grid. The analysis process is executed using a statistical method called Hierarchical Cluster Analysis.

Key Words: Information Systems, Knowledge Acquisition, Repertory Grid

Authors:
Mohammed Abbas Shouman, profshouman@hotmail.com
Mohammed Gaber Abou ľAli, m_abouali59@yahoo.com
Ayman Mohammed Mostafa, eng_ayman_m@hotmail.com

Editor: Amjad D. Al-Nasser, amjadn@yu.edu.jo

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